INPICTURE SEARCH ALGORITHM
summer project pal Active In SP Posts: 308 Joined: Jan 2011 
22012011, 06:13 PM
INPICTURE SEARCH ALGORITHM
B.Tech Seminar Report by Anand Babu N B Department of Computer Science and Engineering Government Engineering College, Thrissur December 2010 INPICTURE SEARCH ALGORITHM.pdf (Size: 321.52 KB / Downloads: 57) Abstract In this advanced world researchers are more interested in searching for fragments that are similar to a query, than a total data item that is similar to a query; the search interest is for contains, not is. This paper presents an O(log n)algorithm, called the generalized virtual node (GVN)algorithm. The GVN algorithm is a search algorithm for data fragments that have similar contents to that of a query. Each image is transformed into characteristic features and these features are stored in a hierarchical multidimensional structure, called a ktree. The experimental results of this inpicture search algorithm on an image database demonstrate a search quality is qualitatively and quantitatively acceptable, with a retrieval time faster than other algorithms, such as bruteforce and Partial Matching. Chapter 1 Introduction Image (multimedia) data query can be classified into two different approaches: • awholepicture (awholeobject) search • inpicture (inobject) search Each approach generates a different type of query result. Awholepicture or thumbnail based search approach searches for data that is globally similar to the query input; on the other hand, an inobject search approach searches for a large piece of data contains a fragment that is similar to the query. An example of awholepicture search is to find a picture in a database using the picture or its thumbnail image as a query. An example of inpicture search is to find a picture that contains parts that are similar to the query, where the query is a part of an image regardless what the backgrounds are. Most of the recent work in the field of multimedia retrieval emphasizes the a wholeobject search approach ; only a few researchers are working on inobject search approach . Chapter 2 KTREE INDEX STRUCTURE A ktree is a directed graph.Each node has 2k incoming edges and one outgoing edge with a balanced structure. The structure of the ktree is feature independent.Therefore, the positions of the nodes in the tree are always the same, no matters what features are. Figure 2.1 shows the comparison between using ktree and Rtree structures as indices by using two different features. Compared to other featuredependent index structure (illustrated in Figure 2.2), using the ktree approach to search every feature altogether takes shorter computing time than using featuredependent structure to search on many indices individually, merge all results,and filter them with spatial constraints. The generalized indexing/retrieval model The ktree structure is used to retain location information and a histogram is used to store the characteristics of each portion the data that corresponds to a part of the tree. This generalized model is depicted in Figure 3. First, either general mathematical models, or special methods extract the feature of interest. Second, the domain of datatype is reduced into a set and each item in the database is also mapped to the set. Third, virtual data values are added to data items, if necessary, to create such that each item will generate a balanced ktree. A ktree is built using histogram values for each feature. 


summer project pal Active In SP Posts: 308 Joined: Jan 2011 
22012011, 06:22 PM
InPicture Search Algorithm
ANAND BABU.N.B. 2K7705 Overview Abstract Introduction Ktree index structure Rtree index structure Advantages and Comparison of Ktree The Generalized Indexing/Retrieval Model Visualisation of Retrieval Model Virtual Node Concept InPicture Search Algorithm Illustration Conclusion InPicture Search Algorithm presentation.pdf (Size: 702.06 KB / Downloads: 46) ABSTRACT Researchers are currently more interested in searching for fragments that are similar to a query, than a total data item that is similar to a query; the search interest is for “contains”, not “is”. This paper presents an O(log n)algorithm, called the “generalized virtual node (GVN)”algorithm. The GVN algorithm is a search algorithm for data fragments that have similar contents to that of a query. INTRODUCTION Image (multimedia) data query can be classified into two different approaches: •awholepicture (awholeobject) search •inpicture (inobject) search It uses a universal model that is able to represent the characteristic features of any multimedia datatype. KTREE INDEX STRUCTURE A ktree is a directed graph. Each node has 2k incoming edges and one outgoing edge with a balanced structure. ADVANTAGES OF KTREE The structure of the ktree is feature independent. Since a ktree is a hierarchical data structure, multiresolution processing can be exploited into this structure. The complexity of data structure affects only the degree k of the tree. The ktreebased feature index for a feature can be used for many types of queries. 


